Sumanth Raj Urs + realfast blog agent
Jun 9, 2025
Salesforce just dropped something massive. Their new Agentforce flex credits pricing model isn't just an update - it's a complete reimagining of how you pay for AI work.
The old model? $2 per conversation, whether your agent did meaningful work or just chatted. The new model? 10 cents per action - and you only pay when real work gets done.
The fundamental shift: from conversations to actions
Here's what changed. Salesforce moved from charging you for every conversation to charging you only when your agent performs actual work. Actions include:
Triggering flows
Making API calls
Executing generative AI solutions
Reading from or writing to systems
Idle chitchat? Free. Decision-making and intent detection? Free. You pay only when your agent moves the needle.
What does this actually cost?
We analyzed real customer data to understand what this pricing means in practice:
Simple FAQ queries: Around 10-30 cents per interaction. Your agent finds the answer, delivers it, handles basic follow-up questions.
Complex multi-step processes: Between 80 cents to $1.20. These involve authentication, checking multiple systems, executing several workflows.
The $2 conversation equivalent: We haven't found one yet. Even complex internal productivity use cases rarely hit that threshold.
Most use cases sit between 1-5 actions. The outliers that go higher are truly exceptional.
Why this pricing model wins
The old conversation model had a fundamental problem. You needed two things to make purchase decisions: clarity on ROI and predictable scaling costs.
The $2 conversation price gave you predictability - if you expected 10,000 support tickets, you knew your cost. But you had no idea if those conversations would actually solve problems or just burn budget on meaningless exchanges.
The new action-based model flips this. You pay for work done. When your agent authenticates a user, queries your database, and updates a record - that's work. When it thinks through which workflow to trigger - that's included for free.
Watch the entire podcast here
The ROI calculation changes everything
Here's where it gets interesting. ROI calculations become both more complex and more meaningful.
You need to know your current operational costs. What does a support ticket cost you today? What about loan collection calls? Order processing?
Then you analyze your data. Not all tickets are equal - some need human intervention, others can be fully automated. You're probably automating the 30th percentile complexity tickets while your current costs reflect the 95th percentile.
This detailed analysis reveals the real opportunity. Factor in employee churn, retraining costs, and scaling challenges - the numbers start looking very compelling.
Salesforce lowers the barriers
Salesforce is serious about adoption. They're giving you 100,000 free flex credits (roughly 5,000 actions) if you're on Unlimited or Enterprise editions.
Even bolder? They're letting you convert existing licenses into flex credits. This isn't just a new pricing model - it's Salesforce betting their revenue on Agentforce being the future.
From proof of concept to proof of value
Traditional software implementations focus on use cases and features. Agent implementations must focus on metrics and outcomes.
The old approach: Build something that works according to spec, deploy it, measure value months later.
The new approach: Operationalize an agent in 30-45 days, measurably impact one specific metric, prove ROI immediately.
This isn't about showing that agents work - everyone knows they work. It's about proving they're worth the investment on your specific data with your specific processes.
The digital workforce reality
Here's what nobody talks about: AI agents need management just like human employees.
Your agents need performance reviews, monitoring, and continuous training. When an agent underperforms, you need to diagnose why - missing knowledge articles, flawed reasoning, inadequate data access.
This creates an entirely new category of work: agent management. And the only scalable way to manage hundreds of agents? Use other agents to do it.
These "eval" agents act like QA managers - continuously testing performance, identifying issues, suggesting improvements. It's agents managing agents, all the way down.
What makes agent implementation different
Traditional software is deterministic. Same input, same output. Agents are probabilistic - they can surprise you.
This changes everything about implementation:
Agent persona matters: Your service agent and your sales agent need different personalities. One solves problems, one identifies opportunities. Get this wrong and your service agent starts pushing products to frustrated customers.
Job descriptions need detail: You can't just say "handle customer support." You need specific workflows, success criteria, security protocols, approval processes. Think of it as writing the most detailed job description ever.
Monitoring is continuous: Unlike traditional software that either works or doesn't, agents require ongoing performance management.
The path forward
If these changes excite you, here's what you should do:
Start with your data. Analyze your current operational costs and identify processes suitable for automation. Look for high-volume, repeatable tasks where humans spend time on predictable workflows.
Use those 100,000 free credits wisely. Don't build a demo - build something that moves a real business metric. Measure it. Prove it works.
Focus on internal use cases first. Salesforce is launching unlimited usage SKUs for employee-facing agents. This is where you'll see the biggest immediate returns.
The bottom line
Salesforce Agentforce flex credits represents more than new pricing. It's the shift from paying for software licenses to paying for digital labor.
You're not buying tools anymore. You're hiring digital employees who work 24/7, never need training, and scale instantly.
The question isn't whether this pricing model is better - it obviously is. The question is how quickly you can capitalize on the advantage before everyone else figures it out.
The game just changed. Are you ready to play?
